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        <title>Concept-Best-Matching: Evaluating Compositionality In Emergent Communication</title>
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    <abstract>Artificial agents that learn to communicate in order to accomplish a given task acquire communication protocols that are typically opaque to a human. A large body of work has attempted to evaluate the emergent communication via various evaluation measures, with **compositionality** featuring as a prominent desired trait. However, current evaluation procedures do not directly expose the compositionality of the emergent communication. We propose a procedure to assess the compositionality of emergent communication by finding the best-match between emerged words and natural language concepts.The best-match algorithm provides both a global score and a translation-map from emergent words to natural language concepts. To the best of our knowledge, it is the first time that such direct and interpretable mapping between emergent words and human concepts is provided.</abstract>
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%0 Conference Proceedings
%T Concept-Best-Matching: Evaluating Compositionality In Emergent Communication
%A Carmeli, Boaz
%A Belinkov, Yonatan
%A Meir, Ron
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand and virtual meeting
%F carmeli-etal-2024-concept
%X Artificial agents that learn to communicate in order to accomplish a given task acquire communication protocols that are typically opaque to a human. A large body of work has attempted to evaluate the emergent communication via various evaluation measures, with **compositionality** featuring as a prominent desired trait. However, current evaluation procedures do not directly expose the compositionality of the emergent communication. We propose a procedure to assess the compositionality of emergent communication by finding the best-match between emerged words and natural language concepts.The best-match algorithm provides both a global score and a translation-map from emergent words to natural language concepts. To the best of our knowledge, it is the first time that such direct and interpretable mapping between emergent words and human concepts is provided.
%U https://aclanthology.org/2024.findings-acl.189
%P 3186-3194

Markdown (Informal)

[Concept-Best-Matching: Evaluating Compositionality In Emergent Communication](https://aclanthology.org/2024.findings-acl.189) (Carmeli et al., Findings 2024)

• Concept-Best-Matching: Evaluating Compositionality In Emergent Communication (Carmeli et al., Findings 2024)

ACL

• Boaz Carmeli, Yonatan Belinkov, and Ron Meir. 2024. Concept-Best-Matching: Evaluating Compositionality In Emergent Communication. In Findings of the Association for Computational Linguistics ACL 2024, pages 3186–3194, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.